Pandas groupby multiple fields then diff

by

First, sort the DataFrame and then all you need is groupby.diff():

df = df.sort_values(by=['site', 'country', 'date'])

df['diff'] = df.groupby(['site', 'country'])['score'].diff().fillna(0)

df
Out: 
         date    site country  score  diff
8  2018-01-01      fb      es    100   0.0
9  2018-01-02      fb      gb    100   0.0
5  2018-01-01      fb      us     50   0.0
6  2018-01-02      fb      us     55   5.0
7  2018-01-03      fb      us    100  45.0
1  2018-01-01  google      ch     50   0.0
4  2018-01-02  google      ch     10 -40.0
0  2018-01-01  google      us    100   0.0
2  2018-01-02  google      us     70 -30.0
3  2018-01-03  google      us     60 -10.0

sort_values doesn’t support arbitrary orderings. If you need to sort arbitrarily (google before fb for example) you need to store them in a collection and set your column as categorical. Then sort_values will respect the ordering you provided there.

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